Conventional treatment for mental disorders follows a diagnosis in accordance with a standard followed by selection of a treatment reported to be effective for that particular diagnosis. Typically there are several treatment options available. The selection of a particular treatment depends on the judgement of a physician. The soundness of this judgement, in turn, depends on the information available to the physician. The information available to the physician often includes risk of allergic responses and the like in the event a substance is administered as part of the treatment. However, little else is at hand to help the physician avoid prescribing a treatment to which the patient is non-responsive or worse, a treatment that aggravates the mental illness rather than control it. Thus, physicians attempt numerous treatment modalities in order to determine an effective treatment in a given case.
Heterogeneity of treatment response of diagnosed mental illness is well known. Accordingly, there have been attempts to improve the diagnostic methods to identify more homogeneously responsive groupings of particular mental disorders. Yet, despite the increased homogeneity of diagnosed mental illness within and across practitioners, response to treatment of mental disorders continues to be markedly heterogeneous.
Presently, the Diagnostic and Statistical Manual of Mental Disorders (“DSM”) provides definitive guidelines for diagnosing and treating mental disorders. See, e.g., Nathan et al.: “Psychopathology: Description and Classification” in Annual Reviews of Psychology, 50:79-107 (1999). The DSM manual, presently in its fourth edition, commonly referred to as “DSM-IV,” is organized along various axes. For instance, axis I disorders include major depression and schizophrenia; axis II includes personality disorders; while axis III addresses physical disorders contributing to psychological symptoms. A convenient view of the DSM entries is in accordance with its chapters since they are topically organized to avoid excessive details. Such details are within the plurality of diagnoses described in each of the chapters. Example chapters include those on ‘childhood disorders,’ ‘eating disorders,’ ‘substance-related disorders,’ ‘anxiety,’ ‘mood disorders’ and the like.
Another, alternative standard for diagnosing mental disorders is the set of criteria maintained by the World Health Organization (“WHO”) as the International Classification of Diseases (“ICD”). ICD is employed more extensively in Europe than North America, although, DSM-UV remains the predominant international standard for allowing independent health providers to make similar diagnoses of a particular patient despite the inherently subjective nature of the underlying observations.
Applying the aforesaid standard diagnostic techniques requires data collection. At present there are available various methods of data collection, such as objective measures of brain activity or patient interviews and observations of subject's stimulated or natural behavior. For instance, objective measures such as recordings from the electrodes attached to the head of a subject, termed electroencephalograms (“EEG”), have long been available. However, they have had very limited use outside the context of monitoring and controlling seizures or studying sleep related disorders.
Notably, known systems for diagnosing mental disorders, such as DSM-UV, do not employ EEG recordings to aid in either diagnosis or treatment of a mental disorder other than in the context of seizures, brain death, intraoperative monitoring or dementia. For instance, a committee of experts in an article, Hoffman et al., J. of Neuropsychiatry and Clinical Neurosciences, 11:3 (1999), cites the American Academy of Neurology (“AAN”) as recommending quantitative EEG (“QEEG”) as being of no clinical value in 1987 and in 1997 as being of limited clinical use in (a) stroke, (b) dementia, (c) intraoperative monitoring, and (d) epilepsy. However, clinical utility was not accepted by AAN for application in (a) traumatic brain injury, (b) psychiatric disorders including learning disabilities, and (c) medical-legal use. While Hoffman et al. disagree with the AAN's limited recommendations for use of QEEG, they do not offer concrete alternatives for therapeutic application of QEEG in treating mental disorders. This is illustrative of the challenges posed by objective data such as neurometric/neurophysiologic information in general and EEG data in particular in treating mental disorders.
The neurophysiologic technique of EEG measures the electrical activity of the brain as a function of time varying spontaneous potentials (SP) through a number of electrodes placed at standard locations on the scalp. The neurophysiologic information obtained through EEG analysis is recorded as sets of traces of the amplitude of SP over time for scalp electrodes that are variably referenced. This analog EEG information can then be visually analyzed and interpreted for signal abnormalities.
In the 1970's, quantitative analysis of the EEG signal provided rapid easy access to measurements that extended the EEG method beyond qualitative visual detection of signal abnormality. Quantitative EEG (QEEG) studies involve the multi-channel acquisition, processing, and analysis of brain activity often but not exclusively by computers. An example of an EEG/QEEG instrument is the Easy Writer II system, available from Caldwell Laboratories, Inc. (Kennewick, Wash.).
In one version of EEG/QEEG recordings electrodes (at least one electrode, preferably nineteen electrodes and most preferably 21 electrodes) are commonly placed at standard locations on the scalp using the International 10/20 Placement System. A multi-channel recording of the brain's activity in an alert, awake, eyes-closed, or “background” state is then recorded and analyzed often by use of Fast Fourier Transform (FFT) signal processing. FFT processing of the raw EEG permits measurement and quantification of multiple characteristics of brain electrical activity. In this process, optionally, signals due to muscle or eye movement or environmental noise are rejected, leaving information related to neurophysiology for further analysis.
EEG recordings are typically of uncertain quality and often require the aid of an experienced technician. See, e.g., Nuwer, Marc, “Assessment of digital EEG, quantitative EEG, and EEG brain mapping: Report of the American Academy of Neurology and the American Clinical Neurophysiology Society” in Neurology, 49:277-292 at 279 (1997). Still, there are known methods for obtaining EEG data reliably by placing electrodes (satisfying specified impedance limits) relative to well-defined landmarks on the skull such as the International 10/20 system. U.S. Pat. No. 5,730,146 issued to Itil et al. on Mar. 24, 1998 discloses an apparatus for reproducibly placing electrodes, in accordance with the International 10/20 system, on the head of a subject and transmitting EEG data to a remote location over a telephone connection. U.S. Pat. No. 5,816,247 issued to Douglas E. Maynard on Oct. 6, 1998 discloses an apparatus and method for collecting EEG signals from a subject and subjecting the signals to sorting with the aid of a suitably trained neural network.
Not everyone with an abnormal EEG has an associated disorder—mental or otherwise. While EEG reveals gross changes such as spikes and disturbances accompanying seizures or the lack of brain activity associated with death, it is less than successful in providing a correlation with known mental disorders as defined by DSM-UV or its other editions. Similar difficulties are associated with correlating EEG/QEEG findings with other mental disorder diagnosis systems, such as the ICD.
DSM-IV manual has many detractors who disagree with various methodological details or conclusions therein as well as the basic strategy underlying the manual. However, in view of the reality of mental disorders and the therapeutic benefit possible with administration of substances and therapy to a subject to treat mental disorders such criticism does not provide practical alternatives to prescribing substances or treatment other than DSM-IV or a comparable diagnostic scheme. The previously mentioned lack of reliance on EEG recordings in making diagnosis reflects the lack of correlation between a diagnosis in accordance with the known systems for diagnosing mental disorders, such as DSM-IV, and EEG recordings. In the few instances when there is possible a correlation, such as advanced schizophrenia, there are obvious overt disease indicators that eliminate the need for EEG recordings in view of the added expense and technical demands made by EEG.
In addition to EEG, objective measures of brain activity include techniques such as magnetic resonance imaging (MRI), functional magnetic resonance imaging (FMRI), positron emission tomography (PET), single photon emission computerized tomography (SPECT), magnetoencephalography (MEG), quantitative magnetoencephalography (QMEG) and many others. All of these techniques are of limited significance in actual treatment of mental disorders for reasons similar to those discussed in the case of EEG recordings or cost issues or due to ease of use or a combination thereof.
Consequently, known attempts at integrating neurophysiologic information with treatment start with a definitive DSM, or similar, diagnosis followed by an attempt to identify variations in QEEG or EEG that correlate with the known diagnosis. An example of such an approach in the context of a diagnosis of chronic fatigue syndrome is provided by the U.S. Pat. No. 5,267,570 issued to Myra S. Preston on Dec. 7, 1993 for a “Method of Diagnosing and Treating Chronic Fatigue Syndrome.” Similarly, in the context of a diagnosis of Alzheimer's dementia use of EEG data is disclosed by the U.S. Pat. No. 5,230,346 issued to Leuchter et al. on Jul. 27, 1993 for “Diagnosing Brain Conditions by Quantitative Electroencephalography.” Another U.S. Pat. No. 5,873,823 issued to David-Eidelberg on Feb. 23, 1999 discloses a more generalized approach to detect markers to aid in screening patients for traditional diagnosis and treatment. The U.S. Pat. No. 5,083,571 granted to Leslie S. Prichep on Jan. 28, 1992 discloses discriminant and cluster analysis of EEG data in diagnosing mental disorders.
None of the aforementioned patents teaches integration of behavioral definitions of psychiatric disorders with objective data in view of the response of a subject to treatment of the mental state of the patient independent of the diagnosis. Instead, they focus on refining the diagnosis of traditional behavioral psychiatric disorders with the aid of objective data.
It is not unusual for a therapeutic entity prescribed for a particular mental disorder to entirely fail to alleviate the symptoms or to even result in additional or different symptoms. In other words, in addition to weak correlation between traditional diagnostic systems and objective data, the correlation between traditional diagnosis and treatments is also significantly less than desirable.
The absence of a strong correlation between objective data collected from a subject and the known analytic techniques, such as DSM-IV, makes it difficult to discover and utilize the likely utility of a given substance or therapy upon administration to a subject. Indeed, identifying a subject as having an abnormal neurological profile needs a more objective basis than that afforded by subjective data to reduce errors in treatment and improve the likelihood of a successful outcome for a course of treatment.
Moreover, many known substances and currently available therapeutic entities have yet unknown useful effects on the mental state. Reliance on more subjective observational data based on narrated case history or observations often masks useful properties of many known substances. Often, in providing information to modify behavior it is difficult to prospectively persuade a subject that the risk of harm or addiction is greater in the subject's case compared to the general population. Thus, the generation of neurophysiologic information provides a useful tool for designing and implementing outreach programs.
Some substances are of considerable social and political import since the users of such substances are a very small fraction of the general population, and consequently their needs are easily overshadowed by the cost of servicing and locating such users. While the present laws encourage such users through provisions such as identifying “orphan drugs” for special treatment, the cost of identifying even the condition to be targeted by a putative orphan drug poses a challenge. Better identification of orphan drugs would not only improve treatment availability, but actually provide customized treatment to a wide spectrum of subjects.
Moreover, additional substances have addiction associated with their administration. Examples include nicotine, typically self-administered by inhaling fumes, and many other substances whose sale is restricted or prohibited by law. However, educating the public to the dangers posed by such substances is difficult in the absence of a customized risk assessment of deleterious responses and the propensity to exhibit addiction. Presently, there is no method or system for providing such customized yet prospective information as part of public education campaigns and preventive care.
The aforementioned shortcomings are overcome by the present invention, described below, in addition to new capabilities enabled in its various embodiments.